Abstract
Objectives
We examined the cross-sectional association between optimism and cardiovascular health (CVH).
Methods
We used data collected from adults aged 52–84 who participated in the Multi-Ethnic Study of Atherosclerosis (MESA) (n=5,134) during the first follow-up visit (2002–2004). Multinomial logistic regression was used to examine associations of optimism with ideal and intermediate CVH (with reference being poor CVH), after adjusting for socio-demographic factors and psychological ill-being.
Results
Participants in the highest quartile of optimism were more likely to have intermediate [OR=1.51:95%CI=1.25,1.82] and ideal [OR=1.92:95%CI=1.30,2.85] CVH when compared to the least optimistic group. Individual CVH metrics of diet, physical activity, BMI, smoking, blood sugar and total cholesterol contributed to the overall association.
Conclusions
We offer evidence for a cross-sectional association between optimism and CVH.
Keywords: well-being, optimism, cardiovascular health
A recent paradigm shift in cardiovascular epidemiology has occurred from a focus on the singular examination of cardiovascular disease (CVD) risk factors to assessment and consideration of factors involved in the maintenance and promotion of overall cardiovascular health (CVH).1,2 In its recently published document—Strategic Impact Goal Through 2020 and Beyond—the American Heart Association (AHA) seeks a 20% improvement in CVH among all Americans within a 10-year time span, i.e., by the year 2020.2 As defined using AHA standards, CVH is assessed through consideration of seven metrics categorized as health behaviors (diet, smoking, physical activity, BMI) and health factors (blood pressure, blood sugar, total cholesterol). Empirical evidence is accumulating to suggest that favorable CVH profiles are associated with reduced all-cause and cardiac-related mortality,3 decreased cancer incidence,4 enhanced cognitive functioning,5 and greater quality of life.
Researchers have long argued for an important relationship between psychological traits and heart health. Historically, researchers have examined the role of poor psychological functioning as increasing risk of adverse cardiovascular outcomes (e.g., depression and anxiety), but more recently positive psychological characteristics such as dispositional optimism have been considered as possibly conferring protective effects for heart health. Defined as possessing positive outcome expectancy for future events across life domains, dispositional optimism appears to be important for CVD-related outcomes given its positive influence on physiological regulation (e.g., favorable profiles for inflammatory and hemostatic factors) and promotion of healthy lifestyle choices (e.g., physical activity).6,7 When CVD risk factor and health behavior measures are considered individually in cross-sectional and prospective observational studies, positive psychological well-being emerges as a strong predictor for engagement in physical activity,8,9 healthy food consumption,9,10 abstinence from tobacco use,11 and favorable physiological functioning when measuring blood pressure,12–14 glycosylated hemoglobin,15 triglycerides,13,16,17 and body mass index.6,10,18,19 Dispositional optimism has been identified as a potential causal factor for CVD and related outcomes, with evident reduction in risk for coronary heart disease (CHD) with increasing optimism levels.20,21 Prospective studies indicate that optimism is associated with a 50% reduction in CVD risk.6 To our knowledge, no study has examined the association between optimism and the new multicomponent construct of CVH, which offers a novel multisystem exploration that may support a biobehavioral pathway through which well-being influences risk for CHD events and mortality (see Figure 1).Consideration of the new construct of CVH additionally counters the existing scientific discipline that emphasizes disease states by underscoring that health is not the mere absence of disease and that exploration of health assets and protective factors is of import. This new paradigm accentuates primordial prevention instead of disease onset.
Figure 1.
Theoretical model: Psychological well-being and clinical disease
Using data from the Multi-Ethnic Study of Atherosclerosis (MESA), a large multi-center cohort study, we examined the cross-sectional association between optimism and CVH. We hypothesized that persons with higher optimism levels were more likely to have favorable CVH profiles independent of socio-demographic factors and psychological ill-being (e.g., depressive symptoms). The socio-demographic and mental health factors were identified as covariates given their potential to confound the main relationship of interest, with final selection informed by a recently published systematic review documenting important covariates when considering cardiac health in the context of positive psychological well-being.22
METHODS
Study Population and Data Source
MESA is a large multi-center cohort study aiming to conduct an in-depth assessment of subclinical CVD, with particular emphasis on its progression and associated risk factors. Details of the MESA recruitment and study protocol have been published previously. Briefly, original study enrollment occurred from July 2000 to August 2002 across six US regions (Baltimore City and Baltimore County, Maryland; Chicago, Illinois; Forsyth County, North Carolina; Los Angeles County, California; New York, New York; and St. Paul, Minnesota), with inclusion of a total of 6,814 adults between the ages of 45–84. Those with a previous history of symptomatic/clinical CVD were excluded during baseline enrollment. A heterogeneous racial/ethnic composition was achieved with distribution as follows: 38% White, 28% African American, 22% Hispanic/Latino, and 12% Chinese. Participants have been followed across an 11-year time span, with repeat measures taken at 1.5–2 year intervals. There have been 4 repeat assessments to date. Unless noted otherwise, this study used data collected during the first follow-up visit (2002–2004). Approval for the study was obtained through the Institutional Review Boards (IRB) at all participating academic sites.
Analyses for the current study involved 5,134 adult participants. Of the 6,233 participants who attended the first follow up visit, we excluded those who were missing data across main variables of interest, i.e., dispositional optimism (n=56) and participants with incomplete information needed to categorize the seven CVH metrics (n=980). Participants were additionally excluded if they reported an incident CVD-related event prior to the first follow-up visit (n= 63).
Study Measures
Optimism
The Life Orientation Test-Revised (LOT-R) was completed at the first follow-up visit (2002–2004) and used to assess levels of dispositional optimism. The LOT-R is a 6-item self-administered questionnaire with possible scores ranging from 6 (least optimistic) to 24 (most optimistic).23,24 The scale includes three positively worded items (e.g., I’m always optimistic about my future) and three negatively worded items (e.g., I hardly expect things to go my way) that are rated on a 4-point Likert scale with response options ranging from a lot like me to not at all like me. Responses for the negatively worded items were reverse-coded prior to calculation of a composite score, with higher scores indicative of greater optimism. As optimism is characterized by endorsement and rejection across positively and negatively worded items, we did not consider the 3-item subscales of the LOT-R, but instead decided on unidimensional treatment as recommended.25,26 Given the lack of clinically-based cutoffs for the LOT-R, quartiles were created as this resulted in more equitable distribution of participants across scores; previous studies using the MESA cohort have employed use of quartiles.7 Adequate internal consistency for the LOT-R was evident in the current study with an overall Cronbach alpha of 0.73.
Cardiovascular Health
Details of the MESA study protocol and assessment methods have been published elsewhere. Briefly, former and current smoking status was determined from self-report. A food frequency questionnaire adapted from the Insulin Resistance Atherosclerosis Study survey was used to evaluate dietary intake.27 Adapted from the Cross-Cultural Activity Participation Study, physical activity was subjectively assessed using a detailed self-report survey instrument.28 BMI (kg/m2) was calculated from staff-ascertained measures of weight and height. After a 12-hour fast, blood was drawn (~40 ml) to obtain lipid profiles and fasting glucose values. Congruent across study sites, three systolic and diastolic blood pressure readings were taken with participants in the seated position; mean values were obtained by averaging the last two readings.29,30 Self-reported medication use was also considered when identifying those with pre-existing diabetes mellitus, hypercholesterolemia, and hypertension. Information on dietary intake was obtained during the baseline assessment; the remaining CVH metrics were evaluated using data from the first follow-up visit.
Cardiovascular health was assessed with the following seven metrics: smoking status, diet, physical activity, body mass index (BMI), fasting plasma glucose, serum cholesterol, and blood pressure. Each metric was scored and categorized as poor, intermediate, and ideal as specified by AHA recent recommendations, with consideration of medication use (i.e., antihypertensive, lipid-lowering, and hypoglycemic) where appropriate.2 Points were allocated for each of the seven metrics with scores of 0 (poor), 1 (intermediate) or 2 (ideal)for each health behavior (diet, smoking, physical activity, BMI) and health factor (blood pressure, blood sugar, total cholesterol). A total CVH score was computed by summing across metrics to derive a score that could range from 0 to 14, with higher scores indicative of better cardiovascular health. This composite CVH score was further categorized into poor (0–7 points), intermediate (8–11 points), and ideal (12–14 points), which is consistent with previously published classification methods for total CVH.31
Covariates
Covariates included age, sex (i.e., male; or female), race/ethnicity (i.e., Caucasian; Chinese-American; African American; or Hispanic), marital status, education, income, health insurance status (i.e., insured; or not-insured), and psychological ill-being. Categorical values were created for marital status (i.e., married/living as married/living with a partner; or other [widowed, divorced, separated, or never married]), education (i.e., less than high school; high school; some college; bachelor degree; or graduate/professional degree), and income (i.e., less than $40,000; or ≥ $40,000). All socio-demographic information was collected using self-report questionnaires completed in person at the first follow-up assessment (2002–2004). Psychological ill-being was assessed using the Mental Health Composite Scale of the 12-item Short Form Health Survey (SF-12).32 Scores for mental health range from 0 to 100, with lower scores indicative of poor mental health. Physical health was assessed using self-report measures, i.e., Physical Health Composite Scale of the SF-1232 and inquiry of diagnosed medical conditions of arthritis, liver and kidney disease.
Statistical Analyses
The continuous composite score for optimism was used to create quartiles across the full range of the observed distribution. Descriptive characteristics are presented by quartile of optimism. Group differences in participant characteristics across optimism quartiles were examined using an F-test or χ2-test as appropriate. Age-, sex-, and race-adjusted mean optimism scores were computed for the composite CVH measure and individual metrics across classification groups (i.e., ideal, intermediate, poor); F-tests were used for comparison across groups.
The association between optimism and the composite CVH score was examined using multinomial logistic regression. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated for the prevalence of intermediate and ideal CVH (versus poor CVH), across quartiles of optimism. The lowest quartile of optimism (i.e., the least optimistic) served as the reference category. Three separate models were constructed. Model 1 was unadjusted. Model 2 adjusted for age, sex, race/ethnicity, marital status, education, income, and insurance status. Model 3 additionally adjusted for psychological ill-being. In sensitivity analyses, multivariate Model 2 was re-examined with additional inclusion of covariates capturing self-reported measures of physical health, i.e., physical health composite scale of SF-12 and medical comorbidities of arthritis, liver and kidney disease. Additional sensitivity analyses employing multinomial logistic regression treated dispositional optimism as a continuous score ranging from 6 to 24 when modeling its association with composite CVH categories (poor CVH vs. intermediate or ideal).
All data analyses were conducted using statistical software (SAS 9.1 for Windows; SAS, Inc, Cary, North Carolina).
RESULTS
Characteristics of the study sample
Table 1 provides participant characteristics according to level of optimism. The p-values for overall trend across socio-demographic characteristics are presented by quartile of optimism. Participants categorized as most optimistic tended to be older and reported more favorable mental health. Race/ethnicity, income, education and health insurance status differed by optimism level. A greater proportion of African American and Hispanic/Latino participants were in the highest optimism quartile as compared with the lowest quartile, while this trend was reversed for White and Chinese participants. Compared to the least optimistic participants, greater levels of income and education were reported by those in the highest optimism quartile. Finally, as compared to the least optimistic, a slightly greater proportion of uninsured participants were classified as most optimistic.
Table 1.
Characteristics of the Study Sample According to Quartile of Optimism: MESA (N=5,134)
N=5,134 | Optimism Quartile | ||||
---|---|---|---|---|---|
Least Optimistic |
Mid-Low Optimistic |
Mid-High Optimistic |
Most Optimistic |
||
Quartile of LOT-R Score (Optimism) | I n=1611 |
II n=1522 |
III n=1118 |
IV n=883 |
pb |
Age, M (SD) | 63.5 (10.5) | 63.0 (10.1) | 63.6 (9.8) | 64.2 (10.1) | 0.04 |
Sex | |||||
Women, n (%) | 872 (54.1) | 781 (51.3) | 596 (53.3) | 476 (53.9) | 0.41 |
Race/Ethnicity, n (%) | |||||
Caucasian | 670 (41.6) | 654 (43.0) | 518 (46.3)* | 297 (33.6)* | <0.0001 |
Chinese-American | 199 (12.4) | 191 (12.6) | 111 (9.9) | 95 (10.8)* | |
African American | 368 (22.8) | 368 (24.2) | 304 (27.2)* | 244 (27.6) | |
Hispanic | 374 (23.2) | 309 (20.3) | 185 (16.6) | 247 (28.0) | |
Marital Status | |||||
Married/Living as married/Living with a partner | 968 (60.2) | 954 (62.7) | 711 (63.7) | 564 (63.9) | 0.18 |
Othera | 640 (39.8) | 568 (37.3) | 406 (36.4) | 319 (36.1) | |
Annual Income, n (%) | |||||
Less than 40K | 852 (52.9) | 716 (47.0) | 452 (40.4) | 423 (47.9) | <0.0001 |
≥ 40K | 759 (47.1) | 806 (53.0)* | 666 (59.6)* | 460 (52.1)* | |
Education, n (%) | |||||
Less than high school | 314 (19.5) | 209 (13.7) | 139 (12.4) | 170 (19.3) | <0.0001 |
High school | 378 (23.5) | 261 (17.2) | 145 (13.0) | 133 (15.1) | |
Some college | 437 (27.2) | 448 (29.4)* | 326 (29.2)* | 245 (27.8) | |
Bachelor degree | 240 (14.9) | 297 (19.5)* | 240 (21.5)* | 159 (18.0) | |
Graduate or professional degree | 239 (14.9) | 307 (20.2)* | 267 (23.9)* | 176 (19.9)* | |
Health Insurance Status, n (%) | |||||
Has health insurance | 1521 (94.4) | 1417 (93.1) | 1050 (93.9) | 801 (90.7)* | 0.003 |
Does not have health insurance | 90 (5.6) | 105 (6.9) | 68 (6.1) | 82 (9.3) | |
SF-12 Health Survey, M (SD) | |||||
Mental Health Index | 48.3 (10.0) | 52.7 (7.8) | 54.1 (7.3) | 55.8 (6.6) | <0.0001 |
Includes those reporting being widowed, divorced, separated, or never married.
P-value examining overall group differences using χ2 or F tests as appropriate.
Multinomial regression model(s) treating least optimistic as the referent group along with the socio-demographic categories of Hispanic, male, not-insured, less than high school, and income < 40K; used to examine between-group differences with a p-value < 0.05.
Association of optimism with cardiovascular health measures
Distribution of the CVH measures by optimism quartile are presented in Table 2. A significantly higher mean composite CVH score was observed with increasing levels of optimism, ranging from7.57 among the least optimistic to 8.13 among the most optimistic. Optimists displayed more favorable CVH profiles with greater likelihood for classification into intermediate and/or ideal categories across multiple health behaviors and factors.
Table 2.
Distribution of Total Cardiovascular health (CVH) and Subcomponents by Quartile of Optimism: MESA (N=5,134)
Optimism Quartile | |||||
---|---|---|---|---|---|
Least Optimistic |
Mid-Low Optimistic |
Mid-High Optimistic |
Most Optimistic |
||
Quartile of LOT-R Score (Optimism) |
I n=1611 |
II n=1522 |
III n=1118 |
IV n=883 |
pb |
Total CVH Scorea, M (SD) | 7.57 (2.49) | 7.96 (2.43) | 8.06 (2.41) | 8.13 (2.31) | <0.0001 |
CVH, n (%) | |||||
Poor | 774 (48.1) | 637 (41.9) | 458 (41.0) | 334 (37.8) | <0.0001 |
Intermediate | 752 (46.7) | 791 (52.0)* | 569 (50.9)* | 485 (54.9)* | |
Ideal | 84 (5.2) | 94 (6.2) | 90 (8.1)* | 64 (7.3)* | |
Diet | |||||
Poor | 731 (45.4) | 623 (40.9) | 418 (37.4) | 309 (35.0) | <0.0001 |
Intermediate | 802 (49.8) | 807 (53.0)* | 622 (55.6)* | 511 (57.9)* | |
Ideal | 78 (4.8) | 92 (6.0)* | 78 (7.0)* | 63 (7.1)* | |
Smoking | |||||
Poor | 217 (13.5) | 168 (11.0) | 106 (9.5) | 73 (8.3) | 0.0005 |
Intermediate | 653 (40.5) | 671 (44.1)* | 490 (43.8)* | 366 (41.5)* | |
Ideal | 741 (46.0) | 683 (44.5) | 522 (46.7)* | 444 (50.3)* | |
Physical Activity | |||||
Poor | 476 (29.6) | 342 (22.5) | 238 (21.3) | 212 (24.0) | <0.0001 |
Intermediate | 300 (18.6) | 265 (17.4) | 182 (16.3) | 154 (17.4) | |
Ideal | 835 (51.8) | 915 (60.1)* | 698 (62.4)* | 517 (58.6)* | |
Body Mass Index | |||||
Poor | 560(34.8) | 484 (31.8) | 331 (29.6) | 258 (29.2) | 0.02 |
Intermediate | 608 (37.7) | 581 (38.2) | 471 (42.1) | 362 (41.0) | |
Ideal | 443 (27.5) | 457 (30.0) | 316 (28.3) | 263 (29.8) | |
Blood Pressure | |||||
Poor | 773 (48.0) | 708 (46.5) | 560 (50.1) | 419 (47.5) | 0.62 |
Intermediate | 297 (18.4) | 279 (18.3) | 205 (18.3) | 168 (19.0) | |
Ideal | 541 (33.6) | 535 (35.2) | 353 (31.6) | 296 (33.5) | |
Blood Sugar | |||||
Poor | 250 (15.5) | 202 (13.3) | 135 (12.1) | 110 (12.5) | 0.04 |
Intermediate | 275 (17.1) | 286 (18.8)* | 177 (15.8) | 160 (18.1) | |
Ideal | 1086 (67.4) | 1034 (67.9) | 806 (72.1)* | 613 (69.4)* | |
Total Cholesterol | |||||
Poor | 494 (30.7) | 439 (28.8) | 305 (27.3) | 218 (24.7) | 0.01 |
Intermediate | 425 (26.4) | 373 (24.5) | 305 (27.3) | 262 (29.7)* | |
Ideal | 692 (43.0) | 710 (46.7) | 508 (45.4) | 403 (45.6)* |
Continuous CVH scores range from 0–14 with higher scores representing better CVH.
P-value examining overall group differences using χ2 or F tests as appropriate.
Multinomial regression model(s) treating categories of poor CVH and least optimistic as the referent group to examine between-group differences; p < 0.05.
This finding is supported by Figure 2 which presents the proportion of participants classified as ideal across the CVH metrics based upon optimism quartile. Although not a completely graded response is evident, across most health metrics, a greater proportion of individuals have an ideal health classification with increasing optimism scores.
Figure 2.
Proportion in Ideal Classification Group across Metrics by Optimism Quartile. P-values for comparison across groups based on Chi-square tests.
Table 3 presents the odds ratios and associated confidence intervals for having intermediate or ideal CVH according to quartile of optimism, with poor CVH serving as the referent category. In unadjusted models and when compared to the least optimistic group, participants in the highest quartile of optimism showed50% higher odds of being in the intermediate versus poor CVH category (95% CI=1.26, 1.78) and 76% higher odds of being in the ideal versus poor CVH category(95% CI=1.24, 2.50).These associations were strengthened after adjustment for socio-demographic factors (Model 2); those in the highest quartile had 55% higher odds of having intermediate CVH (95% CI=1.29, 1.85) and twice the odds of having ideal CVH (95% CI=1.45, 3.06). Similar results were observed in the multivariable adjusted model accounting for ill-being. In sensitivity analyses, adjustment for self-reported physical health and medical comorbidities mildly attenuated the results, with documented maintenance of a robust association between optimism and CVH (not shown).
Table 3.
Multivariable Association Between Optimism and Cardiovascular Health (N= 5,128)
Cardiovascular Health | ||
---|---|---|
Intermediate vs. Poor |
Ideal vs. Poor |
|
6-item LOT-R | ||
OR (95% CI) | OR (95% CI) | |
M1: Unadjusted | ||
Quartile I—Lowest | 1.0 (ref) | 1.0 (ref) |
Quartile II | 1.28 (1.11, 1.48) | 1.36 (0.99, 1.86) |
Quartile III | 1.28 (1.10, 1.50) | 1.81 (1.32, 2.49) |
Quartile IV—Highest | 1.50 (1.26, 1.78) | 1.76 (1.24, 2.50) |
M2: Minimally Adjusteda | ||
Quartile I—Lowest | 1.0 (ref) | 1.0 (ref) |
Quartile II | 1.21 (1.04, 1.40) | 1.24 (0.89, 1.73) |
Quartile III | 1.19 (1.01, 1.41) | 1.76 (1.26, 2.48) |
Quartile IV—Highest | 1.55 (1.29, 1.85) | 2.11 (1.45, 3.06) |
M3: Multivariable Adjustedb | ||
Quartile I—Lowest | 1.0 (ref) | 1.0 (ref) |
Quartile II | 1.19 (1.02, 1.39) | 1.18 (0.84, 1.65) |
Quartile III | 1.17 (0.99, 1.39) | 1.64 (1.15, 2.33) |
Quartile IV—Highest | 1.51 (1.25, 1.82) | 1.92 (1.30, 2.85) |
Quartiles range from lowest (I) to highest (IV) for the LOT-R measure, with Quartile IV corresponding to the highest levels of optimism for the full 6-item LOT-R measure.
Adjusted for age, gender, race/ethnicity, marital status, education, income, and insurance status.
Adjusted for age, gender, race/ethnicity, marital status, education, income, insurance status, and mental health (SF-12).
Table 4 presents the association between continuous scores of dispositional optimism and CVH categories. As before, a three-category modeling scheme was used to examine CVH; poor [0–7 points] (ref), intermediate (8–11 points), and ideal (12–14 points). In the multivariable adjusted model, one SD increase in dispositional optimism was associated with 13% [95% CI = 1.06, 1.21] higher odds of being in intermediate health and 15% [95% CI = 1.003, 1.32] higher odds for classification into ideal health, when treating poor CVH as the referent category for the modeling procedure. As before, inclusion of psychological ill-being as a covariate only slightly attenuated the observed associations. Differences were not observed for dispositional optimism scores (19.8 vs. 19.9, p = 0.39), but on average, less favorable CVH profiles were evident for participants with missing values across the main variables of interest.
Table 4.
Odds ratios and 95% confidence intervals (CIs) for the cross-sectional association of one standard deviation increase in optimism score with cardiovascular health (N= 5,128)
Cardiovascular Health | ||
---|---|---|
Intermediate vs. Poor | Ideal vs. Poor | |
6-item LOT-R | ||
OR (95% CI) | OR (95% CI) | |
M1: Unadjusted | 1.17 (1.10, 1.24) | 1.28 (1.13, 1.44) |
M2: Minimally Adjusteda | 1.14 (1.08, 1.21) | 1.21 (1.06, 1.37) |
M3: Multivariable Adjustedb | 1.13 (1.06, 1.21) | 1.15 (1.003, 1.32) |
Adjusted for age, gender, race/ethnicity, marital status, education, income, and insurance status.
Adjusted for age, gender, race/ethnicity, marital status, education, income, insurance status, and mental health (SF-12).
DISCUSSION
There was a statistically significant positive cross-sectional association between dispositional optimism and CVH, with the most optimistic participants exhibiting twice the odds of having ideal CVH profiles in unadjusted analyses. This association remained significant even after adjustment for socio-demographic characteristics (i.e., age, sex, race/ethnicity, marital status, education, income, and insurance status) and psychological ill-being. Secondary analyses identified the associations of optimism with individual CVH metrics of diet, physical activity, BMI, smoking, blood sugar and total cholesterol as contributing to the overall association.
Although this is the first study to consider the association between optimism and CVH as defined by the American Heart Association,2 our results are generally consistent with evidence derived from studies considering the relationship between dispositional optimism and single cardiac-related health behaviors and/or factors. Previous cross-sectional and longitudinal evidence links optimism to more favorable dietary9,10 and physical activity8,9,33 profiles, and reduced likelihood for smoking.6,11,34,35 Reports on the relationship between optimism and BMI are less consistent.8–10
These findings notwithstanding, it is worth noting that cross-sectional and longitudinal studies have yielded somewhat inconsistent findings on the association of dispositional optimism with metabolic and physiologic measures (e.g., glycated hemoglobin, lipids and blood pressure).6 Unlike our findings with the MESA cohort, Brody et al.36 did not find an association between optimism and glycemic control in a sample of 200 African American adults with type 2 diabetes. Discordant findings may be a consequence of dissimilar study measures (i.e., fasting glucose in mg/dl vs. HbA1C) and divergent participant samples (i.e., diabetic individuals of African American descent vs. a heterogeneous cohort with and without diabetes). Additionally, the LOT-R scoring rubric used by Brody et al.36 focused on identifying participants with low levels of optimism and did not consider effects across the continuum of optimism levels. The relatively small sample (n = 200) of African American adults with type 2 diabetes may further explain the null findings, particularly if insufficient power was achieved to detect the association of interest, i.e., low optimism and HbA1C. Contributing to the current state of knowledge in the area of positive psychological well-being and glycemic control, the current study, the first to utilize a large (n = 5,134) heterogeneous adult cohort, documents a robust association between optimism and fasting glucose levels. This is also applicable in relation to findings on the association between optimism and lipid levels, as limited and discordant findings are also reported to date.9,13
Longitudinal studies document protective effects of optimism-related measures (i.e., hope, curiosity, vitality) on incident hypertension across a 1-year time span.12,13 However, several cross-sectional studies report an inverse association between dispositional optimism and blood pressure,14 while others document null findings.6,37 Racial/ethnic heterogeneity of the MESA sample, particularly inclusion of underserved minority populations (i.e., African Americans and Hispanic/Latinos), may inform our null finding. Raikkonen and Matthews38 found a robust association between optimism and ambulatory blood pressure in a sample of middle-aged working non-Hispanic Whites, while no such finding was evident in a more diverse adolescent sample that included African American participants.37 Results for the MESA cohort are consistent with that reported for racial/ethnic minority adolescents, with similarities in racial/ethnic composition potentially explaining congruent findings. If racial/ethnic minorities more frequently experience chronic daily stressors such as racial discrimination, it is possible that this may obscure the effects of an individual’s life orientation on single-day assessments of blood pressure, particularly if stressful events serve to temporarily increase blood pressure.
Future studies will want to consider the mechanism through which dispositional optimism may influence the metrics used to construct the CVH score, particularly as the difference in CVH between the least and most optimistic subgroups, i.e., 0.56 points, may be of clinical significance as it approximates the 1-point difference associated with an 8% reduction in stroke risk.39 At the population level, even this moderate difference in CVH score translates into a significant reduction in subsequent deaths. In terms of mechanism, one possibility is that optimists employ more adaptive coping skills when faced with adversity.40 For example, optimists are more likely to engage in active problem-focused coping and positive reinterpretation of stress evoking events, while infrequently employing tactics of denial and avoidance.41,42 In turn, these positive coping responses have been found to be predictive of greater likelihood of engaging in prudent health behaviors—i.e., tobacco avoidance and moderate alcohol use—and attainment of favorable physical health profiles.40
Although additional work is necessary, our findings offer support—through assessment of the new construct of CVH—for the hypothesized biobehavioral mechanism through which optimism favorably impacts CVD-related endpoints. Major CVD risk factors (e.g., hypercholesterolemia, hypertension, diabetes, obesity)—considered when deriving the CVH score—have substantial evidence linking them to progression of subclinical atherosclerosis, clinical manifestation of CVD, and subsequent CVD-related mortality.43 Thus, the mechanism whereby psychological well-being influences CVD-related outcomes may well be both behavioral and biologic in nature, through favorable impact on engagement in healthy behavior (e.g., high levels of physical activity) and enhanced regulation of metabolic and cardiovascular functioning (e.g., improved glucose metabolism).44
The present study has multiple strengths. It is the first to examine the association of dispositional optimism and CVH in a large (n=5,134) ethnically/racially diverse sample of adults. This allowed for examination of effect modification by race/ethnicity, yielding no apparent interaction of race/ethnicity with dispositional optimism when regressed upon CVH metrics. A well-validated instrument was used to assess dispositional optimism and standardized approaches were used to obtain objective measures of the health factors, i.e., blood pressure, blood sugar, and total cholesterol. However, study limitations should be considered when interpreting findings. Measurement error and misclassification bias are plausible for dietary intake and physical activity as they were self-reported. As with all cross-sectional studies, we are unable to make definitive inferences about causality. Specifically, it is possible that individuals are more optimistic because they are healthier. Longitudinal studies are needed to establish causality and adequately address uncertainties regarding temporality of the association. Finally, future studies should examine differential item functioning when using the LOT-R with diverse ethnic/racial subgroups, particularly as we observed a greater proportion of African American and Hispanic/Latino participants in the highest optimism quartile as compared with the lowest quartile.
IMPLICATIONS FOR HEALTH BEHAVIOR
The current study found a significant positive association between dispositional optimism and CVH. This evidence suggests that, primordial-, primary-, and secondary-prevention strategies through modification of psychological well-being (e.g., optimism) may be a potential avenue in helping to reach AHA’s goal to increase cardiovascular health by 20% before 2020. As evidence suggests that 40% of individual variance in happiness—a hedonistic construct of psychological well-being—is determined by intentional activities under direct human volition,45–47 current evidence, in conjunction with implementation of randomized clinical trials will further aid in determining whether successful alteration of psychological well-being favorably impacts CVH behaviors and factors. Indeed, mutable psychological factors (e.g., optimism) are evident for which public health interventions may be of benefit.
Acknowledgements
This research was supported by contracts N01-HC-95159, N01-HC-95160, N01-HC-95161,N01-HC-95162, N01-HC-95163, N01-HC-95164, N01-HC-95165, N01-HC-95166,N01-HC-95167, N01-HC-95168 and N01-HC-95169 from the National Heart, Lung, and Blood Institute and by grants UL1-TR-000040 and UL1-TR-001079 from NCRR. The authors thank the other investigators, the staff, and the participants of the MESA study for their valuable contributions. A full list of participating MESA investigators and institutions can be found at http://www.mesa-nhlbi.org. Rosalba Hernandez was a T32 Post-Doctoral Fellow on NHLBI T32 HL-069771-10 (Daviglus, PI).
Footnotes
Human Subjects Statement: The Multi-Ethnic Study of Atherosclerosis (MESA) was approved by the institutional review boards at each of the study sites.
Conflicts of Interest Disclosures: The authors declare that they have no conflict of interest with respect to the data reported herein.
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